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Classical simulations of noisy variational quantum circuits

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arxiv 2306.05400 v1 pith:5VBZ6R5W submitted 2023-06-08 quant-ph

classification quant-ph
keywords circuitsalgorithmerrornoisyquantumclassicalefficientlowesa
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Noise detrimentally affects quantum computations so that they not only become less accurate but also easier to simulate classically as systems scale up. We construct a classical simulation algorithm, LOWESA (low weight efficient simulation algorithm), for estimating expectation values of noisy parameterised quantum circuits. It combines previous results on spectral analysis of parameterised circuits with Pauli back-propagation and recent ideas for simulations of noisy random circuits. We show, under some conditions on the circuits and mild assumptions on the noise, that LOWESA gives an efficient, polynomial algorithm in the number of qubits (and depth), with approximation error that vanishes exponentially in the physical error rate and a controllable cut-off parameter. We also discuss the practical limitations of the method for circuit classes with correlated parameters and its scaling with decreasing error rates.

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Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Scaling Quantum Algorithms via Dissipation: Avoiding Barren Plateaus

    quant-ph 2025-07 conditional novelty 6.0 of 10

    Dissipative quantum circuits with periodic qubit resets provably avoid both unitary and noise-induced barren plateaus for gates near the final measurement.

  2. Scalable Simulation of Quantum Many-Body Dynamics with Or-Represented Quantum Algebra

    quant-ph 2025-06 conditional novelty 6.0 of 10

    ORQA, a Pauli-string based simulation framework, is parallelized to run on Fugaku with up to 2^17 processes, tracking over a trillion Pauli strings and reproducing kicked Ising results.

  3. Out of Tune: Demystifying Noise-Effects on Quantum Fourier Models

    quant-ph 2025-06 conditional novelty 5.0 of 10

    Noise, especially decoherent gate errors, systematically reduces Fourier coefficient magnitudes, expressibility, and entangling capability of quantum Fourier models, with circuit architecture and encoding modulating t...

  4. Pauli Propagation: A Computational Framework for Simulating Quantum Systems

    quant-ph 2025-05 conditional novelty 5.0 of 10

    Pauli propagation, a classical method that evolves Pauli operators through quantum circuits, is presented as a unified algorithmic framework together with the Julia package PauliPropagation.jl that implements it.

  5. Artificial intelligence for representing and characterizing quantum systems

    quant-ph 2025-09 unverdicted novelty 1.0 of 10

    A review organizes AI-based quantum system characterization into ML, deep learning, and language model paradigms, covering property prediction and implicit state reconstruction.

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